Name: Causal Inference in R: The Whole Game - Malcolm Barrett, Stanford University [Pre-Registration Required]
Start: 2024-07-02T20:30:00+0200
End: 2024-07-02T21:30:00+0200

The Sched app allows you to build your schedule for the useR! Virtual Event. The virtual event is free; there is no cost to participate.

Virtual Tutorials will take place live on Zoom, and you must pre-register in order to participate. You will be able to use the chat and Q&A features in Zoom to ask the presenters questions. Please register by clicking on the link in the tutorial’s description.

Virtual Session Presentations will take place on YouTube Premier. Speakers will be available during the presentation to answer questions in the chat. The presentations can be found in this playlist.

Please note: This schedule is automatically displayed in Central European Summer Time (UTC+02:00). To see the schedule in your preferred timezone, please select from the drop-down located at the bottom of the menu to the right.

IMPORTANT NOTE: Timing of sessions and room locations are subject to change.

The in-person program will take place in Salzburg, Austria, on 8-11 July. Please see the in-person schedule page for more information.

Tuesday July 2, 2024 20:30 - 21:30 CEST

Zoom

Tutorial Registration

In this tutorial, I’ll present an overview of our book, Causal Inference in R, freely available at r-causal.org. We’ll discuss the whole game, so to speak, of causal inference, following a few key steps: 1. Specify a causal question 2. Draw our assumptions using a causal diagram 3. Model our assumptions 4. Diagnose our models 5. Estimate the causal effect, and 6. Conduct sensitivity analysis on the effect estimate. We’ll discuss some new tools in the causal inference ecosystem, such as tipr, ggdag, propensity, halfmoon, and more, each making the act of causal inference easier and more principled.

Speakers

Malcolm Barrett

Research Software Engineer, Stanford University

Malcolm Barrett is an epidemiologist and research software engineer at Stanford University. After receiving his Ph.D. in epidemiology from the University of Southern California, he worked as a data scientist at Apple and Posit. His work has focused on causal inference methodology... Read More →

Tuesday July 2, 2024 20:30 - 21:30 CEST
Zoom

Virtual Tutorial, Statistical Methods

Virtual useR! 2024

Malcolm Barrett

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